Application of AdamSPGD algorithm to sensor-less adaptive optics in coherent free-space optical communication system.

Area of Science:

• Optical communication systems
• Adaptive optics
• Atmospheric turbulence compensation

Background:

• Stochastic Parallel Gradient Descent (SPGD) is used for sensor-less adaptive optics in free-space optical communication.
• SPGD suffers from slow convergence and local optima, limiting its effectiveness.
• Atmospheric turbulence degrades the performance of optical communication systems.

Purpose of the Study:

• To propose a novel algorithm, AdamSPGD, that combines adaptive moment estimation with SPGD for efficient wavefront correction.
• To enhance the convergence speed, robustness, and dynamic capabilities of sensor-less adaptive optics systems.
• To mitigate the adverse effects of atmospheric turbulence on optical communication quality.

Main Methods:

• Developed the AdamSPGD algorithm by integrating adaptive moment estimation with the SPGD algorithm.
• Conducted theoretical analysis and numerical simulations to evaluate algorithm performance.
• Performed experimental validation to confirm simulation results and assess practical applicability.

Main Results:

• AdamSPGD demonstrated significantly increased convergence speed compared to traditional SPGD.
• The algorithm showed improved robustness and dynamic performance in wavefront correction.
• Experimental results indicated a reduction of approximately 50% in required iterations.
• AdamSPGD effectively suppressed atmospheric turbulence effects on mixing efficiency, bit error rate, and outage probability.

Conclusions:

• AdamSPGD offers a substantial improvement over existing SPGD methods for sensor-less adaptive optics.
• The enhanced performance makes AdamSPGD suitable for improving the quality of coherent free-space optical communications.
• This algorithm provides a more efficient solution for real-time wavefront correction in dynamic environments.